Metaheuristics optimization of financial trading strategies for single asset trading / Abdeslem Derdour (2023) 

Public ISBD Titre : Metaheuristics optimization of financial trading strategies for single asset trading Type de document : document électronique Auteurs : Abdeslem Derdour, Auteur ; Mohamed Tadjine, Directeur de thèse Editeur : [S.l.] : [s.n.] Année de publication : 2023 Importance : 1 fichier PDF (6.1 Mo) Présentation : ill. Note générale : Mode d'accès : accès au texte intégral par intranet. Mémoire de Projet de Fin d’Études : Automatique : Alger, École Nationale Polytechnique : 2023 Bibliogr. P. 83 - 86. - Annexe. P. 75 - 82. Langues : Anglais (eng) Mots-clés : Walk Forward Optimization (WFO) Particle Swarm Optimizer (PSO) Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) Low Frequency Technical Trading Systems (LFTTS) Crypto-currencies Index. décimale : PA03223 Résumé : The study focused on optimizing technical trading systems using metaheuristic techniques, such as Particle Swarm Optimization and Multi-Objective Evolutionary Algorithms. The results indicate that these methods significantly enhance the performance and robustness of the trading systems. Traditional training approaches were found to be susceptible to overfitting, a concern that was mitigated through WalkForward Optimization. The choice of the objective function was highlighted as crucial in improving system robustness. It is recommended that practitioners carefully select the objective functionand optimization method for designing and evaluating technical trading systems. Metaheuristics optimization of financial trading strategies for single asset trading [document électronique] / Abdeslem Derdour, Auteur ; Mohamed Tadjine, Directeur de thèse . - [S.l.] : [s.n.], 2023 . - 1 fichier PDF (6.1 Mo) : ill. Mode d'accès : accès au texte intégral par intranet. Mémoire de Projet de Fin d’Études : Automatique : Alger, École Nationale Polytechnique : 2023 Bibliogr. P. 83 - 86. - Annexe. P. 75 - 82. Langues : Anglais (eng) Mots-clés : Walk Forward Optimization (WFO) Particle Swarm Optimizer (PSO) Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) Low Frequency Technical Trading Systems (LFTTS) Crypto-currencies Index. décimale : PA03223 Résumé : The study focused on optimizing technical trading systems using metaheuristic techniques, such as Particle Swarm Optimization and Multi-Objective Evolutionary Algorithms. The results indicate that these methods significantly enhance the performance and robustness of the trading systems. Traditional training approaches were found to be susceptible to overfitting, a concern that was mitigated through WalkForward Optimization. The choice of the objective function was highlighted as crucial in improving system robustness. It is recommended that practitioners carefully select the objective functionand optimization method for designing and evaluating technical trading systems.

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Code-barres	Cote	Support	Localisation	Section	Disponibilité	Spécialité	Etat_Exemplaire
EP00697	PA03223	Ressources électroniques	Bibliothèque centrale	Projet Fin d'Etudes	Disponible	Automatique	Téléchargeable

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DERDOUR Abdeslem.pdf URL